I am a practical developer. I do have my favorite programming languages (Ruby, Haskell, Clojure, and Java) but I tend to look first at what libraries are available in different languages for whatever project I am currently working on.
I did a lot of work in machine learning in the 1980s (mostly in neural networks) and since then I have probably spent about 15% of my work time directly working on machine learning problems. That has changed in the last few years since several of my consulting customers wanted help spinning up on machine learning.
I have used Scala a fair amount but it has never been a "favorite language," mostly because I didn't care for the tooling. Now I find myself motivated to use Scala because of the awesome Apache MLlib and Breeze machine learning libraries. Also, I have solved my "tooling problem" for Scala development; if you are interested here is my setup: I use a remote high-memory, high-CPU server instance for fast builds. I used to use IntelliJ for Scala development but now I just keep a SBT console open and use Emacs with Ensime and sbt-mode using SSH shells. This is a simple setup but now I am happier using Scala.
I have also been spending a fair amount of time with Google's TensorFlow deep learning tools and the easiest path to solving problems with TensorFlow is working in Python. If you are interested, I do almost all of my work with Python using the free community edition of PyCharm.
So, in general I am trying to avoid the "want to use my favorite programming language trap." The joy is in solving problems and not in wanting to use a favorite language and software stack.